From this post by Ricardo Tellez:
OpenAI has released the Gym, a toolkit for developing and comparing reinforcement learning (RL) algorithms. That toolkit is a huge opportunity for speeding up the progress in the creation of better reinforcement algorithms, since it provides an easy way of comparing them, on the same conditions, independently of where the algorithm is executed.
The toolkit is mainly aimed at the creation of RL algorithms for a general abstract agent. Here, we are interested in applying it to the control of robots (of course!). Specifically, we are interested in ROS based robots. That is why, in this post we describe how to apply the OpenAI Gym to the control of a drone that runs with ROS
Let’s see an example of training.
The drone training example
In this example, we are going to train a ROS based drone to be able to go to a location of the space moving as low as possible (may be to avoid being detected), but avoiding obstacles in its way.
For developing the algorithm we are going to use the ROS Development Studio (RDS). That is an environment that allows to program with ROS and its simulations with a web browser, without having to install anything on the computer. So we have all the required packages for ROS and OpenAI Gym and Gazebo simulations already installed.
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